# Topside Ionosphere and Plasmasphere Modelling Using GNSS Radio Occultation and POD Data

^{*}

^{†}

## Abstract

**:**

## 1. Introduction

## 2. Dataset

## 3. Method

#### 3.1. Climatological Modeling

#### 3.2. Background Construction

#### 3.3. Tomographic Reconstruction

## 4. Results

#### 4.1. General Distributions

#### 4.2. Residuals

#### 4.3. Assessment Using Ionosonde Data

#### 4.4. Assessment Using DMSP Data

#### 4.5. Assessment Using Van Allen Probes Data

^{3}and the NeQuick RMSE was 11.03 × 10${}^{8}$ el/m${}^{3}$. The total RMSE using the RBSP-B instrument was 8.05 × 10${}^{8}$ el/m${}^{3}$ for tomography and 10.98 × 10${}^{8}$ el/m${}^{3}$ for NeQuick. The developed method thus resulted in an improvement of 26%.

#### 4.6. Assessment Using METOP Data

## 5. Conclusions

## Author Contributions

## Funding

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**General patterns of the estimated values of NmF2 (10${}^{12}$ el/m${}^{3}$), hmF2 (km) and topside VTEC (10${}^{16}$ el/m${}^{2}$). The days of 2013 are related to days of year (DOY) 172, 264 and 356 for the Northern solstice, equinox and Southern solstice, respectively. DOYs of 2018 are related to 180, 264 and 359 for the Northern solstice, equinox and Southern solstice, respectively. These are the closest DOYs to the seasons of interest with actual COSMIC observations.

**Figure 2.**Meridional cross-sections during solstices and equinoxes of 2013 (

**top panels**) and 2018 (

**bottom panels**). The unit of the color bar is el/m${}^{3}$.

**Figure 3.**Overview of the residuals of the developed method in comparison to RO peak electron density and satellite-based TEC. The left panel shows the temporal series of the standard deviations and daily averages of the errors computed for 2013 and 2018. The right panel shows the histogram of normalized occurrences of the errors, with the corresponding mean ($\mu $) and standard deviation ($\sigma $) of the differences.

**Figure 4.**Critical frequency estimated in five ionosonde locations using the GIRO dataset (

**left**), tomography (

**middle**) and NeQuick (

**right**) in terms of local time and the days of the year 2013. White spaces represent lack of data.

**Figure 5.**Critical frequency estimated in five ionosonde locations using GIRO dataset (

**left**), tomography (

**middle**) and NeQuick (

**right**) in terms of local time and day of year of 2018. White spaces represent lack of data.

**Figure 6.**Peak height estimated in five ionosonde locations using GIRO dataset (

**left**), tomography (

**middle**) and NeQuick (

**right**) in terms of local time and day of year of 2013. White spaces represent lack of data.

**Figure 7.**Peak height estimated in five ionosonde locations using GIRO dataset (

**left**), tomography (

**middle**) and NeQuick (

**right**) in terms of local time and day of year of 2018. White spaces represent lack of data.

**Figure 8.**Histograms of foF2 and hmF2 errors from tomography and NeQuick when compared to ionosonde data for 2013 (

**left panels**) and 2018 (

**right panels**). The graph also shows model performance in terms of the overall mean ($\mu $) and standard deviation ($\sigma $) of the differences.

**Figure 9.**Electron density and RMSE distributions during 2013 obtained with DMSP number 15, NeQuick and tomography. The electron density Ne (el/m${}^{3}$) was estimated based on a daily average in terms of local time.

**Figure 10.**Electron density and RMSE distributions during 2018 obtained with DMSP number 15, NeQuick and tomography. The electron density Ne (el/m${}^{3}$) was estimated based on a daily average in terms of local time. White spaces are referred to the lack of DMSP or COSMIC data.

**Figure 11.**Electron density errors of the tomography and NeQuick with respect to the DMSP 15 satellite data. The left panel shows the temporal series of the standard deviations and daily averages of the errors computed for 2013 (

**top**) and 2018 (

**bottom**). The right panel shows the histogram of the errors together with the total error mean ($\mu $) and standard deviation ($\sigma $) of the differences.

**Figure 12.**2D histogram of profiles from the Van Allen Probes RBSP-A instrument (

**top left**), tomography (

**top middle**) and NeQuick (

**top right**) as a function of the altitude and logarithm of electron density with base 10. The bottom panels show the corresponding errors of the profiles. The color of the points represents the normalized occurrence.

**Figure 13.**Same as Figure 12, but for the RBSP-B instrument.

**Figure 14.**Histogram of the electron density error for tomography (black line) and NeQuick (blue line) when compared to Van Allen Probes estimations for 2013. The graph also shows the total mean ($\mu $) error and standard deviation ($\sigma $) of the errors.

**Figure 15.**VTEC and RMSE distributions during 2013 estimated with METOP, NeQuick and tomography. VTEC values were taken as a daily average in terms of magnetic latitude. White spaces refer to the lack of METOP or COSMIC data. Units are given in 10${}^{16}$ el/m${}^{2}$.

**Figure 16.**VTEC and RMSE distributions during 2018 estimated with METOP, NeQuick and tomography. VTEC values were taken as a daily average in terms of magnetic latitude. White spaces refer to the lack of METOP or COSMIC data. Units are given in 10${}^{16}$ el/m${}^{2}$.

**Figure 17.**Electron density errors of the tomography and NeQuick with respect to the METOP-A satellite data. The left panel shows the temporal series of the standard deviations and daily averages of the errors computed for 2013 (

**top**) and 2018 (

**bottom**). The right panel shows the histogram of the errors together with the total error mean ($\mu $) and standard deviation ($\sigma $) of the differences.

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**MDPI and ACS Style**

Prol, F.S.; Hoque, M.M.
Topside Ionosphere and Plasmasphere Modelling Using GNSS Radio Occultation and POD Data. *Remote Sens.* **2021**, *13*, 1559.
https://doi.org/10.3390/rs13081559

**AMA Style**

Prol FS, Hoque MM.
Topside Ionosphere and Plasmasphere Modelling Using GNSS Radio Occultation and POD Data. *Remote Sensing*. 2021; 13(8):1559.
https://doi.org/10.3390/rs13081559

**Chicago/Turabian Style**

Prol, Fabricio S., and M. Mainul Hoque.
2021. "Topside Ionosphere and Plasmasphere Modelling Using GNSS Radio Occultation and POD Data" *Remote Sensing* 13, no. 8: 1559.
https://doi.org/10.3390/rs13081559